[config] fix: set the correct max_model_len with YaRN scaling

[AlpinDale]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @AlpinDale, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request addresses an issue where the max_model_len was not being correctly determined, particularly in scenarios involving YaRN scaling. The changes ensure that the system accurately identifies the maximum sequence length for various models, including specific handling for Whisper and Gemma3, by refining the configuration key lookup and rope scaling logic. This fix prevents potential context window miscalculations and improves model compatibility.

Highlights

• Max Model Length Detection: Added 'max_target_positions' to the list of configuration keys checked when determining the maximum model length, specifically to support models like Whisper.
• Gemma3 RoPE Scaling Exclusion: Introduced a special condition to exclude Gemma3 models from the rope scaling adjustment logic, as their 'max_model_len' is already pre-scaled by RoPE.
• Improved RoPE Type Retrieval: Enhanced the retrieval of 'rope_type' by checking both 'rope_scaling.get("rope_type")' and 'rope_scaling.get("type")' to ensure broader compatibility with different configuration formats.

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[gemini-code-assist]

Code Review

This pull request introduces several improvements to model configuration handling. It adds support for max_target_positions to correctly determine the maximum length for Whisper models. Additionally, it enhances the RoPE scaling logic by making it more robust to legacy configuration keys and by correctly excluding gemma3 models, which do not require this scaling. The changes are well-reasoned and improve the codebase's reliability. I have one minor suggestion to make the model type check case-insensitive for better robustness.

[gemini-code-assist]

The check for the gemma3 model type is case-sensitive. To make it more robust, it's advisable to convert the model type to lowercase before the comparison. This will ensure the check works correctly even if the model type is specified with different casing, such as 'Gemma3'.

Suggested change

	):
	).lower():